Robustness of size selection and spectroscopic size, thickness and monolayer metrics of liquid-exfoliated WS2

• Verfasst von: Ueberricke, Lucas [VerfasserIn]
• Verfasst von: Coleman, Jonathan N. [VerfasserIn]
• Verfasst von: Backes, Claudia [VerfasserIn]
• Titel: Robustness of size selection and spectroscopic size, thickness and monolayer metrics of liquid-exfoliated WS2
• Verf.angabe: Lucas Ueberricke, Jonathan N. Coleman, and Claudia Backes
• Fussnoten: Gesehen am 21.09.2018 ; Im Titel ist die "2" tief gestellt.
• Titel Quelle: Enthalten in: Physica status solidi / B
• Jahr Quelle: 2017
• Band/Heft Quelle: 254(2017,11) Artikelnummer 1700443, 9 Seiten
• ISSN Quelle: 1521-3951
• DOI: doi:10.1002/pssb.201700443
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1581178883

Abstract

Liquid exfoliation and centrifugation based size selection has emerged as widely applied technique to produce nanosheets in a solution-processable form. Quantitative spectroscopic metrics to extract nanosheet size, thickness and monolayer content from optical spectra have previously been established. Such metrics are extremely useful and can be used to optimise the production technique (for example on scale-up) and size selection. However, it is not clear whether exfoliation, size selection, and spectroscopic metrics are robust or whether the result depends on the starting material or subtle details of the processing and analysis. By comparing two batches of WS2 exfoliated and size-selected in aqueous surfactant solution using different starting materials, protocols and equipment in each step, we show that the nanosheet size obtained after different steps in a cascade centrifugation is highly reproducible. A detailed statistical analysis on the nanosheet dimensions revealed well-defined relationships between nanosheet mean thickness and monolayer content. Spectroscopic metrics for nanosheet layer number, lateral size (from extinction) and monolayer content (from Raman/photoluminescence) do not depend on sample type and measurement conditions, albeit the data analysis may require adjustment as discussed.